I think research that hits dead ends is not the useless research people are talking about.

there is great work that hit dead ends:
icbinb.cc

publication has a cost, wastes other peoples time to read, verify.
Also, only works in small science fields.
In ML your reputation outside your core community is your google scholar.
Know several people I would never hire but have compelling profiles. people don't call out sloppy work publicly.

Qualitative difference in data quality. OpenDV are youtube dash cams. This is data from real self-driving vehicle sensor stacks.
This should be around 10x the size of prior biggest dataset (the nuPlan split that has sensor data).

Strange, that is a bug in the bluesky preview. The blue link I posted works perfectly fine.

interesting, didn't know that. is there any documentation / paper about how they are using rt-cores for physics acceleration?

not sure if still up to date, but there used to be an exception for universities from the no geforce in clusters rule. we have an old 2080ti cluster.
(wouldn't recommend though they break often. rtx should be the better choice nowadays).

uses raytracing for rendering which requires raytracing cores which these gpus don't have.

Still bad engineering should have the option to run without rendering on A100.

Some chinese folks I talked to mentioned that the local governments are in a fierce competition about who can invest the most money in AI.

h-index is definetly broken but this is making it worse not better.

I now understand the position of the YOLO author a lot better than I did before

comfy design, love it. thanks for the pointer.

would love to see an example of a nice looking robot.
Figure and Tesla are also both cyberpunk style, just not as creepy.

somehow robotics companies don't understand that cyberpunk worlds are cool to watch but terrible to live in.
We need more solarpunk aesthetics in robotics.

And don't forget to cite the paper you are writing ;)